Infopaket

Logic and the Automated Deduction

ННД.16

Обов’язкова дисципліна для ОП

Second

2022/2023

2 Semester

5

PLO3. To master new data tools by processing weblogs, text mining and machine learning, for forecasting business processes and situational management, sentimental analysis of reviews, development of advisory systems for the field of electronic commerce, media, social networks, banking, advertising, etc. PLO4. Analyze big data and model high-level abstractions in large data sets of different nature, design big data repositories to extract data and knowledge, visualize big data, build and evaluate regression models generated based on big data. PLO9. Master methods and technologies of organization and application of data in problems of computational intelligence, build models of decision-making based on the theory of pattern recognition, neural networks and fuzzy logic.

Distance form

To know basic methods of machine learning, mathematical logic, methods of theorem proving in predicate logic, methods of formalization of program systems and systems of Artificial Intelligence. To be able to prove theorems in predicate logic, develop program systems and systems of Artificial Intelligence based on their formal models and prove properties of such systems.

Discipline aim. The purpose of the discipline is to provide up-to-date knowledge of mathematic logic, methods of automated deduction and their application for solving problems of Artificial Intelligence, to develop ability to formulate scientific problem and working hypotheses on the basis of understanding of existing and creation of new holistic knowledge, as well as professional practice, to develop and implement new competitive ideas in the field of information technology. The discipline "Logic and Automated Thinking" is part of the educational program of training specialists at the educational-qualification level "Master" in the field of knowledge 12 "Information Technologies" in the specialty 122 "Computer Science", educational-scientific program "Artificial intelligence". This discipline is mandatory in the specialty 122 "Computer Science", educational-scientific program "Artificial Intelligence". It is taught in the 3rd semester of the 2nd year of master's studies in the amount of 150 hours. (5 ECTS credits) in particular: lectures - 42 hours, consultations - 2 hours, independent work - 106 hours. The course includes 3 parts and 3 tests. The discipline ends with an exam in the 3rd semester.

1. Nikitchenko M.S. Shkilnyak S.S. Prykladna logika. – K., 2013. 2. Nikitchenko M.S. Teoriya programuvannya.– K., 2020. 3. Schneider K.: Verification of Reactive Systems. Formal Methods and Algorithms. – Berlin-Heidelberg: Springer-Verlag, 2004. 4. Nielson H.R. Semantics with Applications: A Formal Introduction / H.R. Nielson, F. Nielson // John Wiley & Sons Inc. P. 240., 1992. 5. Dijkstra E.W. A Discipline of Programming / E.W. Dijkstra // Prentice-Hall, Englewwod Cliffs, New Jersey, 1976.

Lectures, individual work.

Semester assessment: 1. Test 1: LO 1.1, LO 2.2, LO 3.1 – 20 points / 12 points 2. Test 2: LO 1.2, LO 2.2, LO 3.1 – 20 points / 12 points 3. Test 3: LO 1.2, LO 2.2, LO 3.1 – 15 points / 9 points 4. Current evaluation: LO 3.1, LO 4.1, LO 4.2 – 5 points / 3 points Final assessment: - maximum number of points that can be obtained by the student: 40 points; - learning outcomes that are evaluated: LO 1.1, LO 1.2, LO 2.1, LO 2.2, LO 3.1, LO 4.1, LO 4.2 - form of holding: written work.

Ukrainian, English